A 13C-detected 15N double-quantum NMR experiment to probe arginine side-chain guanidinium 15Nη chemical shifts.

Arginine side-chains are often key for enzyme catalysis, protein-ligand and protein-protein interactions. The importance of arginine stems from the ability of the terminal guanidinium group to form many key interactions, such as hydrogen bonds and salt bridges, as well as its perpetual positive charge. We present here an arginine 13Cζ-detected NMR experiment in which a double-quantum coherence involving the two 15Nη nuclei is evolved during the indirect chemical shift evolution period. As the precession frequency of the double-quantum coherence is insensitive to exchange of the two 15Nη; this new approach is shown to eliminate the previously deleterious line broadenings of 15Nη resonances caused by the partially restricted rotation about the Cζ-Nε bond. Consequently, sharp and well-resolved 15Nη resonances can be observed. The utility of the presented method is demonstrated on the L99A mutant of the 19 kDa protein T4 lysozyme, where the measurement of small chemical shift perturbations, such as one-bond deuterium isotope shifts, of the arginine amine 15Nη nuclei becomes possible using the double-quantum experiment

Virtual Homonuclear Decoupling in Direct Detection Nuclear Magnetic Resonance Experiments using Deep Neural Networks

Nuclear magnetic resonance (NMR) experiments are frequently complicated by the presence of homonuclear scalar couplings. For the growing body of biomolecular 13C-detected NMR methods, one-bond 13C–13C couplings significantly reduce sensitivity and resolution. The solution to this problem has typically been to perform virtual decoupling by recording multiple spectra and taking linear combinations. Here, we propose an alternative method of virtual decoupling using deep neural networks, which only requires a single spectrum and gives a significant boost in resolution while reducing the minimum effective phase cycles of the experiments by at least a factor of 2. We successfully apply this methodology to virtually decouple in-phase CON (13CO–15N) protein NMR spectra, 13C–13C correlation spectra of protein side chains, and 13Cα-detected protein 13Cα–13CO spectra where two large homonuclear couplings are present. The deep neural network approach effectively decouples spectra with a high degree of flexibility, including in cases where existing methods fail, and facilitates the use of simpler pulse sequences

Intra-residue methyl-methyl correlations for valine and leucine residues in large proteins from a 3D-HMBC-HMQC experiment

Methyl-TROSY based NMR experiments have over the last two decades become one of the most important means to characterise dynamics and functional mechanisms of large proteins and macromolecular machines in solution. The chemical shift assignment of methyl groups in large proteins is, however, still not trivial and it is typically performed using backbone-dependent experiments in a ‘divide and conquer’ approach, mutations, structure-based assignments or a combination of these. Structure-based assignment of methyl groups is an emerging strategy, which reduces the time and cost required as well as providing a method that is independent of a backbone assignment. One crucial step in available structure-based assignment protocols is linking the two prochiral methyl groups of leucine and valine residues. This has previously been achieved by recording NOESY spectra with short mixing times or by comparing NOESY spectra. Herein, we present a method based on through-bond scalar coupling transfers, a 3D-HMBC-HMQC experiment, to link the intra-residue methyl groups of leucine and valine. It is shown that the HMBC-HMQC method has several advantages over solely using NOESY spectra since a unique intra-residue cross-peak is observed. Moreover, overlap in the methyl-TROSY HMQC spectrum can easily be identified with the HMBC-HMQC experiment, thereby removing possible ambiguities in the assignment

Arginine Side-Chain Hydrogen Exchange: Quantifying Arginine Side-Chain Interactions in Solution

The rate with which labile backbone hydrogen atoms in proteins exchange with the solvent has long been used to probe protein interactions in aqueous solutions. Arginine, an essential amino acid found in many interaction interfaces, is capable of an impressive range of interactions via its guanidinium group. The hydrogen exchange rate of the guanidinium hydrogens therefore becomes an important measure to quantify side-chain interactions. Herein we present an NMR method to quantify the hydrogen exchange rates of arginine side-chain 1 Hϵ protons and thus present a method to gauge the strength of arginine side-chain interactions. The method employs 13 C-detection and the one-bond deuterium isotope shift observed for 15 Nϵ to generate two exchanging species in 1 H2 O/2 H2 O mixtures. An application to the protein T4 Lysozyme is shown, where protection factors calculated from the obtained exchange rates correlate well with the interactions observed in the crystal structure. The methodology presented provides an important step towards characterising interactions of arginine side-chains in enzymes, in phase separation, and in protein interaction interfaces in general

Molecular dynamics simulations of oscillatory Couette flows with slip boundary conditions

The effect of interfacial slip on steady-state and time-periodic flows of monatomic liquids is investigated using non-equilibrium molecular dynamics simulations. The fluid phase is confined between atomically smooth rigid walls, and the fluid flows are induced by moving one of the walls. In steady shear flows, the slip length increases almost linearly with shear rate. We found that the velocity profiles in oscillatory flows are well described by the Stokes flow solution with the slip length that depends on the local shear rate. Interestingly, the rate dependence of the slip length obtained in steady shear flows is recovered when the slip length in oscillatory flows is plotted as a function of the local shear rate magnitude. For both types of flows, the friction coefficient at the liquid-solid interface correlates well with the structure of the first fluid layer near the solid wall.Comment: 31 pages, 11 figure

How functional programming mattered

In 1989 when functional programming was still considered a niche topic, Hughes wrote a visionary paper arguing convincingly ‘why functional programming matters’. More than two decades have passed. Has functional programming really mattered? Our answer is a resounding ‘Yes!’. Functional programming is now at the forefront of a new generation of programming technologies, and enjoying increasing popularity and influence. In this paper, we review the impact of functional programming, focusing on how it has changed the way we may construct programs, the way we may verify programs, and fundamentally the way we may think about programs

Radiative Transfer for Exoplanet Atmospheres

Remote sensing of the atmospheres of distant worlds motivates a firm understanding of radiative transfer. In this review, we provide a pedagogical cookbook that describes the principal ingredients needed to perform a radiative transfer calculation and predict the spectrum of an exoplanet atmosphere, including solving the radiative transfer equation, calculating opacities (and chemistry), iterating for radiative equilibrium (or not), and adapting the output of the calculations to the astronomical observations. A review of the state of the art is performed, focusing on selected milestone papers. Outstanding issues, including the need to understand aerosols or clouds and elucidating the assumptions and caveats behind inversion methods, are discussed. A checklist is provided to assist referees/reviewers in their scrutiny of works involving radiative transfer. A table summarizing the methodology employed by past studies is provided.Comment: 7 pages, no figures, 1 table. Filled in missing information in references, main text unchange

In Situ Monitoring of Intracellular Glucose and Glutamine in CHO Cell Culture

The development of processes to produce biopharmaceuticals industrially is still largely empirical and relies on optimizing both medium formulation and cell line in a product-specific manner. Current small-scale (well plate-based) process development methods cannot provide sufficient sample volume for analysis, to obtain information on nutrient utilization which can be problematic when processes are scaled to industrial fermenters. We envision a platform where essential metabolites can be monitored non-invasively and in real time in an ultra-low volume assay in order to provide additional information on cellular metabolism in high throughput screens. Towards this end, we have developed a model system of Chinese Hamster Ovary cells stably expressing protein-based biosensors for glucose and glutamine. Herein, we demonstrate that these can accurately reflect changing intracellular metabolite concentrations in vivo during batch and fed-batch culture of CHO cells. The ability to monitor intracellular depletion of essential nutrients in high throughput will allow rapid development of improved bioprocesses